ba9714ccee
### What this PR does / why we need it? Optimize qwen2_vl and qwen2_5_vl. ### Does this PR introduce _any_ user-facing change? no ### How was this patch tested? Testing this PR on 1080p picture with tp=1, bs=1 on Qwen2-VL and Qwen2.5-VL, every fa op's during time lasting from 11ms to 9ms, got roughly 22% perf boost. --------- Signed-off-by: zouyida2052 <zouyida@huawei.com> Signed-off-by: zouyida2052 <zouyida2002@gmail.com> Co-authored-by: zouyida2052 <zouyida@huawei.com>
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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import torch
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from vllm.model_executor.layers.activation import QuickGELU, SiluAndMul
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def silu_and_mul_forward_oot(self, x: torch.Tensor) -> torch.Tensor:
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import torch_npu
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out = torch_npu.npu_swiglu(x)
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return out
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def quick_gelu_forward_oot(self, x: torch.tensor) -> torch.Tensor:
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import torch_npu
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out = torch_npu.npu_fast_gelu(x)
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return out
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QuickGELU.forward_oot = quick_gelu_forward_oot
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SiluAndMul.forward_oot = silu_and_mul_forward_oot |